Xuenan Cui
Papers
8
Total Citations
78
H-Index
4
About
Xuenan Cui’s research lies at the intersection of computer vision, sensor fusion, and autonomous mobile robotics, with a focus on enabling robots to perceive, track, and navigate dynamic environments in real time. His most cited work, “A fast feature extraction in object recognition using parallel processing on CPU and GPU” (32 citations), pioneered the use of multi-core and GPU architectures to accelerate feature extraction for real-time object recognition—a critical capability for autonomous mobile robots. Cui has made significant contributions to robust human-robot interaction, developing complementary tracking systems that fuse monocular cameras with laser range finders to overcome challenges like occlusion, illumination change, and camera jitter. His sensor fusion approach for elevator door recognition (9 citations) and person-following algorithms (7 and 4 citations) demonstrate practical solutions for robots operating in cluttered indoor environments. Notably, his INHA localization method (2 citations) uses natural landmarks and homography estimation for reliable robot positioning in lobbies and halls. With a cumulative citation count exceeding 78, Cui’s work has advanced the reliability and efficiency of mobile robot navigation, tracking, and object recognition, laying groundwork for service robots that can seamlessly interact with humans in real-world settings.
Research Focus
Key Achievements
Top Papers
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- 3Robust Elevator Door Recognition using LRF and Camera9 citations · 2012
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- 8Elevator Riding of Mobile Robot Using Sensor Fusion2 citations · 2014